The current systems to aid air navigation generally present raw and complete AIS-MET information in the form of successive messages. Next, the user interprets and mentally filters this received information, based on the situation of the aircraft, so as only to take the relevant data from among the received messages into account.
As an example, the crew of an aircraft receives weather bulletins through an ACARS system (Aircraft Communication Addressing and Reporting System), or by voice transmission if the aircraft is not equipped with the corresponding data link. The crew then prints and analyzes them to assess the current and future meteorological situation of the aircraft.
However, this task constitutes a substantial workload for the user, and involves a relatively long time frame to analyze this AIS-MET information received in the form of successive messages. This task is also fairly tedious and repetitive when the received quantity of data is significant, which further creates a risk of error for the user.